Development of a tomato load/yield monitor

Development of a tomato load/yield monitor The objective of this study was to develop a load/yield monitor for mounting on a processing tomato harvester. A continuous mass flow-ype yield-ensing device equipped with load cells and a vibration-resistant angle transducer along with a differential global positioning system (DGPS) was developed to collect spatially variable yield data in real-time. Both analog and digital signal processing were employed to maximise the accuracy of data acquisition. The yield monitoring system was calibrated, validated, and tested during the 1997 harvesting season. The coefficient of determination, r 2 , between the actual fruit weight and the yield monitor prediction was 0.997. The system was then used to measure yield variability and produce yield maps. There were significant spatial variations in processing tomato yield. The lowest 20% yielding area within a field produced less than half the tomatoes compared to the highest 20% yielding area within the same field. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Computers and Electronics in Agriculture Elsevier

Development of a tomato load/yield monitor

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Publisher
Elsevier
Copyright
Copyright © 1999 Elsevier Science B.V.
ISSN
0168-1699
eISSN
1872-7107
DOI
10.1016/S0168-1699(99)00025-3
Publisher site
See Article on Publisher Site

Abstract

The objective of this study was to develop a load/yield monitor for mounting on a processing tomato harvester. A continuous mass flow-ype yield-ensing device equipped with load cells and a vibration-resistant angle transducer along with a differential global positioning system (DGPS) was developed to collect spatially variable yield data in real-time. Both analog and digital signal processing were employed to maximise the accuracy of data acquisition. The yield monitoring system was calibrated, validated, and tested during the 1997 harvesting season. The coefficient of determination, r 2 , between the actual fruit weight and the yield monitor prediction was 0.997. The system was then used to measure yield variability and produce yield maps. There were significant spatial variations in processing tomato yield. The lowest 20% yielding area within a field produced less than half the tomatoes compared to the highest 20% yielding area within the same field.

Journal

Computers and Electronics in AgricultureElsevier

Published: Aug 1, 1999

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